The space frame has been widely adopted as an aesthetic design feature in architecture. A simple structure space frame can be used as decorative features such as lanterns and hanging features in shopping malls. Repetition of a space frame structure can form large space frames that constitute major element of a building, for example roof cover, canopy, external wall, and even the whole building enclosure. The process of artistic creation of a space frame within resource constraints has always been an issue to architects and designers. Although there are standard proprietary space frame systems with associated computer-aided design, the variety is limited. The current systems are mainly tools for drafting; an intelligent tool for creating original space frame modules is lacking.
The conventional approach to architectural design is for an architect to receive a briefing from a client on functional requirements. Following, it is then up to the architect's skill to convert the client's requirements into building plans. The conversion process is idiosyncratic and very dependent on the skill level of the architect.
It is an object of the present invention to offer an intelligent system used to design space frame modules within resource constraints. The system includes a hybrid methodology made from two core methods, evolutionary algorithm for graph encoding scheme (EAGES) and genetic algorithm (GA). The tool can evolve space frame modules and three-dimensional geometric figures with small number of generations for convergence.